Journal of Physical Activity and Health, 2015, 12, 1508  -1512 http://dx.doi.org/10.1123/jpah.2014-0368 © 2015 Human Kinetics, Inc.

ORIGINAL RESEARCH

Accumulation of Domain-Specific Physical Inactivity and Presence of Hypertension in Brazilian Public Healthcare System Bruna Camilo Turi, Jamile S. Codogno, Romulo A. Fernandes, Xuemei Sui, Carl J. Lavie, Steven N. Blair, and Henrique Luiz Monteiro Background: Hypertension is one of the most common noncommunicable diseases worldwide, and physical inactivity is a risk factor predisposing to its occurrence and complications. However, it is still unclear the association between physical inactivity domains and hypertension, especially in public healthcare systems. Thus, this study aimed to investigate the association between physical inactivity aggregation in different domains and prevalence of hypertension among users of Brazilian public health system. Methods: 963 participants composed the sample. Subjects were divided into quartiles groups according to 3 different domains of physical activity (occupational; physical exercises; and leisure-time and transportation). Hypertension was based on physician diagnosis. Results: Physical inactivity in occupational domain was significantly associated with higher prevalence of hypertension (OR = 1.52 [1.05 to 2.21]). The same pattern occurred for physical inactivity in leisure-time (OR = 1.63 [1.11 to 2.39]) and aggregation of physical inactivity in 3 domains (OR = 2.46 [1.14 to 5.32]). However, the multivariate-adjusted model showed significant association between hypertension and physical inactivity in 3 domains (OR = 2.57 [1.14 to 5.79]). Conclusions: The results suggest an unequal prevalence of hypertension according to physical inactivity across different domains and increasing the promotion of physical activity in the healthcare system is needed. Keywords: motor activity, sedentary lifestyle, health evaluation

Epidemiological studies have indicated that physical inactivity is associated with a variety of noncommunicable diseases, and thus accounts for more than 5 million deaths worldwide each year.1 Hypertension (HTN) is one of the most common noncommunicable diseases affecting almost one-half of the adult population in many countries, including Brazil, where the overall prevalence for the entire population is approximately 20%.2–4 It is a multifactorial, but modifiable, disease with genetic and environmental causes where unhealthy lifestyle, such as physical inactivity, is one of the risk factors predisposing to its occurrence and complications.5 On the other hand, regular practice of physical activity (PA) can decrease the risk of adverse health outcomes and improve chronic health conditions.6 Despite acknowledgment of the health benefits of regular PA, surveillance data from different countries show that overall PA levels remain extremely low.7 In Brazil, approximately 15% of adults are physically inactive, and only 31% meet the minimum recommendations for global PA.8 Although some studies have improved surveillance of noncommunicable diseases and their risk factors in the urban population in Brazil,9–11 limited research has examined the association between physical inactivity in specific domains and HTN, mainly in the public health system. In developing settings, epidemiological data about physical inactivity in occupational, leisure-time and locomotion domains are scarce and thus, it is not clear if physical inactivity in a specific domain could be more harmful to health than another specific one,

Turi ([email protected]) is with Instituto de Biociências, Universidade Estadual Paulista (UNESP), Rio Claro, São Paulo, Brazil. Codogno, Fernandes, and Monteiro are with the Dept of Physical Education, Universidade Estadual Paulista (UNESP), Rio Claro, São Paulo, Brazil. Sui and Blair are with the Dept of Exercise Science, University of South Carolina, Columbia, SC. Lavie is with the Dept of Cardiology, Ochsner Hospital, New Orleans, LA. 1508

as well as it is not clear the burden of the aggregation of physical inactivity in different domains on HTN. The objective of this study, therefore, was to investigate the association between physical inactivity in different domains and the occurrence of HTN among adults users of the Brazilian public healthcare system.

Methods Sample This project was a cross-sectional study conducted from August 2010 to December 2010 in the city of Bauru (the most industrialized region of the country). Before implementation the study was approved by the Ethics Committee Group from Universidade Estadual Paulista, Bauru campus (Process number 1046/46/01/10), and all subjects were asked to sign a standard written consent form. The sample size was estimated based on the percentage of Brazilian population that are covered only by the public health system (60%)12 and using parameters as 3.8% error (arbitrary because there are no other similar studies), 5% statistical significance and design effect of 50%. A sample size of 960 participants was estimated to be representative (minimum of 192 in each Basic Healthcare Unit [BHU]). The city was stratified into 5 geographical regions (south, west, north, east, and center) and the major BHU from each geographical region was selected. Inclusion criteria were defined as: i) age ≥ 50 years; ii) register for at least 1 year at the BHU; iii) have active registration of healthcare service (have performed at least 1 medical visit in the past 6 months). After that, a list with the number of all medical records that reached the inclusion criteria above was made and a random selection was performed until the minimum number of participants (192 in each BHU) is reached. A total of 1915 calls were made and 49.7% (n = 952) were lost for different reasons (did not pick up the phone, incorrect number in the medical record, do not

Physical Inactivity and Hypertension in Brazil   1509



want to participate in the study, scheduled for interview but did not show up). After phone contact, the participants that were selected and agreed to participate of the study came into the BHU to be interviewed, had some physical tests performed (blood pressure, weight and height measurements), and after that data collection (information of the medical records) was held. The final sample size was 963 participants.

age, sex, formal education, economic condition, smoking habit, overweight, SBP, and DBP). In all adjusted multivariable models, after inclusion of potential confounders, the Hosmer-Lemeshow goodness-of-fit test was used to determine how well the model fit the data (nonsignificant results indicate an adequate adjustment). All statistical analyses were performed by the software BioEstat (release 5.0) and statistical significance (p-value) was set at 0.05.

Outcome: Arterial HTN

Results

The occurrence of HTN was based on physician diagnosis identified through the medical records of the participant.

Downloaded by Washington Univ In St Louis on 09/20/16, Volume 12, Article Number 11

Independent Variable: Physical Inactivity The level of PA was estimated using the questionnaire developed by Baecke et al13 (composed of 16 questions scored on a 5-points Likert scale ranging from never to always/very often), which considers 3 domains of PA: Occupational PA (8 questions taking into account intensity and behaviors during work: sitting, standing, walking, lifting heavy loads, sweating, and feeling tired), Sport practice (1 question stratified into 3 questions taking into account intensity, weekly time [in hours], and previous time of practice [in months]), and Leisure-time PA (7 questions taking into account behaviors during leisure-time like play sports, watching television, walking, and cycling). The PA level is calculated by specific equations13 and is expressed as a scores for each PA domain (higher score denotes higher PA) and the sum of all domains constitutes the overall PA. The sample was then divided into quartiles within each domain of PA and participants were classified into 4 groups:14 Physically inactive (≤P25), Moderately Active (P75). Finally, for each participant the number of PA domains classified as “physically inactive” was computed and a categorical variable was created (none, 1, 2, and 3 domains).

Potential Confounders The following data were obtained through interviews and confirmed in medical records: (i) sociodemographic variables (sex, chronological age [structured as categorical variable: 5%). There was an association between physical inactivity in different domains and sex (P = 0.001) and age (P = 0.001) (Table 1). Analyzed in a separate way, physical inactivity in the occupational domain was significantly associated with a higher prevalence of HTN (OR = 1.52 [1.05 to 2.21]). The same pattern occurred for physical inactivity in leisure-time (OR = 1.63 [1.11 to 2.39]) and aggregation of physical inactivity in 3 domains (OR = 2.46 [1.14 to 5.32]) (Table 2). However, in the multivariate-adjusted model, the only variable that remained significantly associated with HTN was the aggregation of physical inactivity in 3 domains (OR = 2.57 [1.14 to 5.79]). It is noteworthy that Hosmer-Lemeshow goodness-of-fit test shown that all models were well fitted to the data (Table 2). Other than that, it was indicated that among the participants with the lowest percentile of physical activity in sports practice and leisure-time domains the occurrence of HTN was higher even after adjustments [OR= 1.67 (1.05 to 2.63) and OR= 1.71 (1.08 to 2.70) respectively]. In addition, considering overall PA, participants who were considered physically inactive (≤P25) presented higher occurrence of HTN [OR= 1.83 (1.12 to 3.01)] (Table 3).

Discussion Our results demonstrated important differences in the distribution of HTN according to accumulation of domain-specific physical inactivity, where being physically inactive in occupational, exercise and leisure-time domains was significantly associated with a higher prevalence of HTN. In the last decade, studies have demonstrated the effect of physical inactivity on major noncommunicable diseases and longevity.1,17 Estimates show that 6% of the burden of coronary heart disease is caused by lack of PA.1 In addition, this behavior has been shown to be consistently associated with increased risk for all-cause, cardiovascular disease (CVD)–related, and all-other-causes mortality in both men and in women.18–21 In addition, a recent meta-analysis with 13 prospective cohort studies indicated inverse dose-response association between levels of recreational PA and risk of HTN.22 A plausible explanation for these several prejudicial health outcomes linked with physical inactivity could be in a suppression of skeletal muscle lipoprotein lipase activity, what can lead to elevated triglycerides levels, promoting poor metabolic health and potent deleterious effects on biologic attributes, particularly lipoproteins,

JPAH Vol. 12, No. 11, 2016

Table 1  Variables Presented According to Number of Domains of Physical Activity in Which the Participant was Classified as Physically Inactive (Bauru, Brazil; n = 963)

Downloaded by Washington Univ In St Louis on 09/20/16, Volume 12, Article Number 11

Independent variables Sex

Female Male

Amount of PA domains in which the participant was classified as physically inactive (≤P25)* None (n = 492) One (n = 291) Two (n = 117) Three (n = 63) 426 (60.3) 180 (25.5) 58 (8.2) 43 (7.8) 66 (25.8) 111 (43.4) 59 (23.1) 20 (7.7)

χ2 test P 0.001

Smoking habit

Yes No

53 (41.7) 439 (52.5)

46 (36.2) 245 (29.3)

21 (16.5) 96 (11.5)

07 (5.5) 56 (6.7)

0.12

Low economic status

Yes No

416 (51.9) 76 (46.9)

236 (29.5) 55 (34.1)

97 (12.1) 20 (12.3)

52 (6.5) 11 (6.8)

0.455

Age

≥65 P25

542 (75.1)

1.00

1.00

 ≤P25

198 (82.2)

1.52 (1.05–2.21)

1.49 (0.95–2.36)

  P-valueHosmer-Lemeshow

0.362 —



 >P25

Sport practice 545 (75.8)

0.219





 ≤P25

195 (79.9)









  P-valueHosmer-Lemeshow Leisure-time

0.015

 >P25

550 (74.9)

1.00

1.00

 ≤P25

190 (83.1)

1.63 (1.11–2.39)

1.49 (0.99–2.26)

  P-valueHosmer-Lemeshow

0.097

Physical inactivity domains

0.004

 None

362 (73.6)

1.00

1.00

  1 domain

228 (78.4)

1.30 (0.92–1.83)

1.18 (0.81–1.74)

  2 domains

95 (81.2)

1.55 (0.93–2.57)

1.35 (0.77–2.38)

  3 domains

55 (87.3)

2.46 (1.14–5.32)

2.57 (1.14–5.79)

  P-valueHosmer-Lemeshow

0.364

Abbreviations: χ2, chi-square test; OR, odds ratio; 95% CI, 95% confidence interval. Note. OR adjusted by Basic Health Care Units, age, sex, formal education, economic condition, smoking habit, overweight, systolic, and diastolic blood pressure. Boldface indicates significance at P < 0.05. 1510

JPAH Vol. 12, No. 11, 2016

Physical Inactivity and Hypertension in Brazil   1511



Table 3  Associations Between Physical Inactivity and Occurrence of Hypertension (Bauru, Brazil; n = 963) χ2 test n (%) Occupational

Binary logistic regression P

ORcrude (95% CI)

ORadjusted (95% CI)

0.357

 ≤P25

197 (82.1)

*

*

  P75

190 (78.5)

*

*

  P-valueH-L

Downloaded by Washington Univ In St Louis on 09/20/16, Volume 12, Article Number 11

Sport practice

0.047

 ≤P25

194 (79.8)

1.52 (1.01–2.32)

1.67 (1.05–2.63)

  P75

174 (72.2)

1.00

1.00 0.126

  P-valueH-L L Leisure time

0.004

 ≤P25

189 (82.9)

1.85 (1.21–2.81)

1.71 (1.08–2.70)

  P75

241 (72.4)

1.00

1.00 0.053

  P-valueH-L Overall PA

0.002

 ≤P25

197 (83.1)

1.98 (1.28–3.08)

1.83 (1.12–3.01)

  P75

171 (71.3)

1.00

1.00 0.075

  P-valueH-L

Abbreviations: χ2, chi-square test; PA, physical activity; OR, odds ratio; 95% CI, 95% confidence interval; H-L, Hosmer-Lemeshow’s test. * Logistic regression was provided only for significant associations according to chi-square test Note. OR adjusted by Basic Health Care Units, age, sex, formal education, economic condition, smoking habit, overweight, systolic, and diastolic blood pressure. Boldface indicates significance at P < 0.05.

which are related to CVD risk.23 In addition, a recent publication found that acute exposure to physical inactivity impairs vascular function, resulting in decreased endothelial function, arterial stiffening, and increased DBP, speculating that inactivity promotes a vascular “deconditioning” state.24 In our findings, physical inactivity in sports and leisure-time domains was significantly associated with higher prevalence of HTN. On the other hand, study conducted among Brazilian adults demonstrated that leisure-time PA reduced the odds of HTN.9 In addition, a recent longitudinal publication examining the relationship between those 2 specific domains with the risk of CVD and mortality in a Chinese population found that only leisure-time PA decreased the risk of CVD events and mortality.25 In addition, a Belgium prospective study found a significantly increased mortality rate between workers who had low levels of both PA types but also in workers combining high occupational PA and low leisure-time PA, confirming the existence of a complex interplay among different PA settings and health outcomes.26 What it means is that high levels of occupational PA do not seem to infer the same preventive effect on CVD and all-cause mortality as high levels of leisure-time PA27 and sports practice. Thus, we have that occupational physical

activity usually has higher vigor, but is performed without guidance, leisure-time physical activity can be beneficial, but not necessarily achieve the PA recommendations, and the sports practice and exercise are generally systematic and structured, obeying duration, intensity and frequency appropriate. In addition, we also found relationship between number of domains classified as physically inactive with age and sex. Aging has contributed to reduced PA in all domains, particularly the leisure-time and work domains.28 Culturally men are encouraged by the family since childhood to sport practice, which does not occur for females.29 Moreover, more women have moved into the labor market over the past few decades and are more likely to be engaged in household PA, which could justify the lower scores in sports and leisure-time PA.30 Actually, a recent publication indicated clustering of inactive behavior in different domains among Brazilian adults, showing that physical inactivity was observed in different contexts according to gender and social variables,31 what can facilitate the occurrence of noncommunicable diseases within this population. As limitations we have i) the use of questionnaire to identify PA levels as opposed to directly measuring PA by pedometers or other devices (thus, some in the population may over-report their

JPAH Vol. 12, No. 11, 2016

1512  Turi et al

Downloaded by Washington Univ In St Louis on 09/20/16, Volume 12, Article Number 11

amount of PA per day because of an increased awareness of the importance of PA); ii) the cross-sectional design that does not allow cause-effect conclusions; iii) the higher number of women in the sample constitutes a statistical limitation, however, this pattern is also observed in national representative surveys; and iv) the absence of dietetic data (eg, sodium and potassium intake) should be taken into account in future studies. Our outcomes point to an unequal prevalence of HTN according to physical inactivity across different domains. Although our findings cannot confirm causal inferences, they indicate the need for further investigation of the complex relationship between physical inactivity in different domains and noncommunicable diseases. Clearly, from a public health perspective, increasing the promotion of PA in the healthcare system and throughout our societies is desperately needed.32 Acknowledgments We thank the Brazilian Federal Agency for Support and Evaluation of Graduate Education—CAPES.

References 1. Lee IM, Shiroma EJ, Lobelo F, et al. Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy. Lancet. 2012;380(9838):219–229. PubMed doi:10.1016/S0140-6736(12)61031-9 2. World Health Organization. A global brief on hypertension. Geneva: author; 2013. 3. World Health Organization. Global status report on noncommunicable diseases 2010. Geneva: author; 2011. 4. Schmidt MI, Duncan BB, Hoffmann JF, et al. Prevalência de diabetes e hipertensão no Brasil baseada em inquérito de morbidade autoreferida, Brasil, 2006. Rev Saude Publica. 2009;43(Supl 2):74–82. PubMed doi:10.1590/S0034-89102009000900010 5. Diaz KM, Shimbo D. Physical activity and the prevention of hypertension. Curr Hypertens Rep. 2013;15:659–668. PubMed doi:10.1007/ s11906-013-0386-8 6. Physical Activity Guidelines Advisory Committee. Physical Activity Guidelines Advisory Committee Report 2008. Washington, DC: US Department of Health and Human Services; 2008. 7. World Health Organization. Global recommendations on physical activity for health. Geneva: author; 2010. 8. Brasil. Ministério da Saúde. Secretaria de Vigilância em Saúde. Secretaria de Gestão Estratégica e Participativa. Vigitel Brasil 2010: vigilância de fatores de risco e proteção para doenças crônicas por inquérito telefônico / Ministério da Saúde, Secretaria de Vigilância em Saúde, Secretaria de Gestão Estratégica e Participativa. Brasília : Ministério da Saúde, 2011. 152 p. Available at: http://bvsms.saude. gov.br/bvs/publicacoes/vigitel_2010.pdf. Accessed September 21, 2013. 9. Perez LG, Pratt M, Simoes EJ, et al. Association between leisure-time physical activity and self-reported hypertension among Brazilian Adults, 2008. Prev Chronic Dis. 2013;10:130032. PubMed doi:10.5888/pcd10.130032 10. Iser BP, Yokota RT, de Sá NN, et al. Protection from chronic diseases and the prevalence of risk factors in Brazilian state capitals-main results from Vigitel 2010. Cien Saude Colet. 2012;17(9):2343–2356. PubMed doi:10.1590/S1413-81232012000900015 11. Moehlecke IBP, Claro RM, Moura EC, et al. Risk and protection factors for chronic non communicable diseases by telephone survey— VIGITEL–2009. Rev Bras Epidemiol. 2011;14(Suppl 1):90–102. PubMed 12. Kilsztajn S, Silva DF, Camara MB, et al. Grau de cobertura dos planos de saúde e distribuição regional do gasto público em saúde. Saúde e Sociedade. 2001;10(2):35–46.

13. Baecke JAH, Burema J, Frijters JER. A short questionnaire for the measurement of habitual physical activity in epidemiological studies. Am J Clin Nutr. 1982;36:936–942. PubMed 14. Codogno JS, Fernandes RA, Sarti FM, et al. The burden of physical activity on type 2 diabetes public healthcare expenditures among adults: a retrospective study. BMC Public Health. 2011;4;11:275. doi:10.1186/1471-2458-11-275 15. Associação Brasileira de Empresas de Pesquisa. Dados com base no Levantamento Sócio Econômico 2008—IBOPE, 2010. Available at: www.abep.org. Accessed March 3, 2010. 16. Lohman TG, Roche AF, Mertorell R. Anthropometric Standardization Reference Manual. Champaign, IL: Human Kinectics Books; 1988. 17. Janssen I, Carson V, Lee IM, et al. Years of life gained due to leisure-time physical activity in the U.S. Am J Prev Med. 2013;44(1):23– 29. PubMed doi:10.1016/j.amepre.2012.09.056 18. Lee IM, Bauman AE, Blair SN, et al. Annual deaths attributable to physical inactivity: whither the missing 2 million? Lancet. 2013;381(9871):992–993. PubMed doi:10.1016/S01406736(13)60705-9 19. Patel AV, Bernstein L, Deka A, et al. Leisure time spent sitting in relation to total mortality in a prospective cohort of U.S. adults. Am J Epidemiol. 2010;172(4):419–429. PubMed doi:10.1093/aje/kwq155 20. Warren TY, Barry V, Hooker SP, et al. Sedentary behaviors increase risk of cardiovascular disease mortality in men. Med Sci Sports Exerc. 2010;42(5):879–885. PubMed doi:10.1249/MSS.0b013e3181c3aa7e 21. Stamatakis E, Hamer M, Dunstan DW. Screen-based entertainment time, all cause mortality, and cardiovascular events: population-based study with ongoing mortality and hospital events follow up. J Am Coll Cardiol. 2011;57(3):292–299. PubMed doi:10.1016/j. jacc.2010.05.065 22. Huai P, Xun H, Reilly KH, et al. Physical activity and risk of hypertension: a meta-analysis of prospective cohort studies. Hypertension. 2013;62(6):1021–1026. PubMed doi:10.1161/HYPERTENSIONAHA.113.01965 23. Bey L, Hamilton MT. Suppression of skeletal muscle lipoprotein lipase activity during physical inactivity: a molecular reason to maintain daily low-intensity activity. J Physiol. 2003;551(2):673–682. PubMed doi:10.1113/jphysiol.2003.045591 24. Nosova EV, Yen P, Chong KC, et al. Short-term physical inactivity impairs vascular function. J Surg Res. 2014;pii:S0022-4804(14)001140. 25. Hu GC, Chien KL, Hsieh SF, et al. Occupational versus leisure-time physical activity in reducing cardiovascular risk and mortality among ethnic Chinese adults in Taiwan. Asia Pac J Public Health. 2014;26(6):604–13. PubMed 26. Clays E, Lidegaard M, De Bacquer D, et al. The combined relationship of occupational and leisure-time physical activity with all-cause mortality among men, accounting for physical fitness. Am J Epidemiol. 2014;179(5):559–566. PubMed 27. Holtermann A, Marott JL, Gyntelberg F, et al. Does the benefit on survival from leisure time physical activity depend on physical activity at work? A prospective cohort study. PLoS One. 2013;8(1):e54548. PubMed doi:10.1371/journal.pone.0054548 28. Livingstone MB, Robson PJ, McCarthy S, et al. Physical activity patterns in a nationally representative sample of adults in Ireland. Public Health Nutr. 2001;4:1107e16. doi:10.1079/PHN2001192 29. Gonçalves H, Hallal PC, Amorim TC, et al. Sociocultural factors and physical activity level in early adolescence. Rev Panam Salud Publica. 2007;22(4):246–253. PubMed 30. Del Duca GF, Rombaldi AJ, Knuth AG, et al. Associação entre nível econômico e inatividade física em diferentes domínios. Rev Brasil Atividade Física Saúde. 2009;14:123e31. 31. Del Duca GF, Nahas MV, de Sousa TF, et al. Clustering of physical inactivity in leisure, work, commuting and household domains among Brazilian adults. Public Health. 2013;127(6):530–537. PubMed doi:10.1016/j.puhe.2013.02.013 32. Vuori IM, Lavie CJ, Blair SN. Physical activity promotion in the health care system. Mayo Clin Proc. 2013;88(12):1446–1461. PubMed doi:10.1016/j.mayocp.2013.08.020

JPAH Vol. 12, No. 11, 2016

Accumulation of Domain-Specific Physical Inactivity and Presence of Hypertension in Brazilian Public Healthcare System.

Hypertension is one of the most common noncommunicable diseases worldwide, and physical inactivity is a risk factor predisposing to its occurrence and...
350KB Sizes 0 Downloads 8 Views